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JRM Vol.26 No.2 pp. 225-235
doi: 10.20965/jrm.2014.p0225
(2014)

Paper:

Minimal Autonomous Mover – MG-11 for Tsukuba Challenge –

Toshiaki Shioya*, Kazushige Kogure*, and Naoya Ohta**

*MITSUBA Corporation, 1-2681 Hirosawa-cho, Kiryu-shi, Gunma 376-8555, Japan

**Gunma University, 1-5-1 Tenjin-cho, Kiryu-shi, Gunma 376-8515, Japan

Received:
December 5, 2013
Accepted:
February 23, 2014
Published:
April 20, 2014
Keywords:
minimum recognition hardware, mobile robot, 2D map matching, binary image processing
Abstract

A design policy for autonomous mobile robots favors widely accepted using as many sensors and as much powerful recognition hardware as possible to realize reliable robot operation. If we plan to use developed technology for commercial products, a separate design policy favors a minimum number of sensors and recognition hardware, i.e., the number enough for reliable operation. We named the robot designed under the latter design policy the Minimal Autonomous Mover (MAM) and built a MAM to participate in the Tsukuba Challenge, a competition for among autonomous mobile robots. In this competition, our robot reached the goal and completed the mission as reported in the sections that follow.

Cite this article as:
T. Shioya, K. Kogure, and N. Ohta, “Minimal Autonomous Mover – MG-11 for Tsukuba Challenge –,” J. Robot. Mechatron., Vol.26, No.2, pp. 225-235, 2014.
Data files:
References
  1. [1] T. Shioya, K. Kogure, and N. Ohta, “Autonomous Travel Robot with Minimal Hardware,” 12th SICE System Integration Division Annual Conf., 202-1, Kyoto University, 2011.
  2. [2] “Tsukuba Challenge 2011 Memorial Symposium Reports,” Toyosu Campus, Shibaura Institute of Technology, 2012.
  3. [3] H. Durrant-Whyte and T. Bailey, “Simultaneous localization and mapping (SLAM): part I,” IEEE Automation Magazine, Vol.13, No.2, pp. 99-110, 2006.
  4. [4] T. Bailey and H. Durrant-Whyte, “Simultaneous localization and mapping (SLAM): part II,” IEEE Automation Magazine, Vol.13, No.3 pp. 108-117, 2006.
  5. [5] T. Tetsuo, M. Satoshi, H. Masataka, S. Masanori, K. Shunsuke, and S. Takashi, “A Robust Localization for Unknown Obstacle Based on the Gridmap Matching,” J. of the Robotics Society of Japan, Vol.30, No.3, pp. 280-286, 2012 (in Japanese).
  6. [6] P. J. Besl and N. D. McKay, “A Method for Registration of 3-D Shapes,” IEEE Trans. on PAMI, Vol.14, No.2, pp. 239-256, 1992.
  7. [7] T. Higuchi, “Particle Filter,” The J. of the Institute of Electronics, Information and Communication Engineers, Vol.88, No.12, pp. 989-994, 2005.
  8. [8] A. Elfes, “Sonar-based real-world mapping and navigation,” IEEE Trans. on Robotics and Automation, Vol.3, No.3, pp. 249-265, 1987.
  9. [9] P. E. Hart, N. J. Nilsson, and B. Raphael, “A formal basis for the heuristic determination of minimum cost paths,” IEEE Trans. on SSC-4, No.2, pp. 100-107, 1968.
  10. [10] K. Kobayashi, Y. Misono, K.Watanabe, T. Okubo, and Y. Kurihara, “Development of Complex Extended Kalman filter based Waypoint Navigation System for Outdoor Environments,” Chino to Joho (J. of Japan Society for Fuzzy Theory and Intelligent Informatics), Vol.21, No.1, pp. 90-99, 2009.
  11. [11] R. G. Brown and P. Y. C. Hwang, “Introduction to random signals and applied Kalman filtering (Second edition),” JohnWiley & Sons, New York, 1992.
  12. [12] Y. Hieida et al., “Realtime SLAM Using L0-Norm Minimization under Dynamic Crowded Environments,” Proc. of the Meeting on Image Recognition and Understanding (MIRU2011), IS3-56, 2011.

  13. Supporting Online Materials:
  14. [a] http://www.ntf.or.jp/challenge/
    [Accessed March 31, 2014]
  15. [b] http://archive.darpa.mil/grandchallenge05/
    [Accessed March 31, 2014]

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Last updated on Nov. 12, 2018